System and Method for Damage Diagnosis

ABSTRACT

The object of the invention is to provide a damage diagnostic system that uses a damage detection system that obtains propagation intensity distribution data, which is expanded in the two dimensions frequency and propagation time, by converting the output value from an oscillation detection sensor that was obtained when oscillation is performed by an oscillator, and for one mode or two or more modes that are selected from the fundamental mode and higher mode of Lamb waves, obtains certain characteristic values from the data, for example three indices, which are the slope of the mode dispersion of the A1 mode (rate of change of the propagation time with respect to the frequency), the amount of decrease in the propagation time of the A1 mode, and the amount of increase in the propagation time of the S0 and S1 modes, and outputs the measurement results. The measurement results are displayed on a display device.

CROSS REFERENCE TO RELATED APPLICATIONS

This application claims priority under 35 U.S.C. 119 based upon JapanesePatent Application Serial No. 2010-058784, filed on Mar. 16, 2010. Theentire disclosure of the aforesaid application is incorporated herein byreference.

FIELD OF THE INVENTION

The present invention relates to a system and method for damagediagnosis that uses Lamb waves.

BACKGROUND OF THE INVENTION

In fields where strength and weight reduction of materials are required,for example in the field of fuselage of an aircraft, in order to meetsuch demands, the use of many composite materials such as CFRP (CarbonFiber Reinforced Plastics) is essential. In order to maintain a highlevel of reliability of structures made from such composite materialsand to perform more efficient design work, damage detection technology(health monitoring technology) is attracting much attention. As devicesfor performing this kind of detection of damage and defects in compositematerials, there are damage detection devices as disclosed in patentpublication 1 and 2 that use a FBG (Fiber Bragg Grating) optical fibersensor. Recently, optical fibers are becoming very thin (for example, 52μm diameter). As a result, even when embedded in a structure, there isnot much of a decrease in strength of the structure. Therefore, opticalfibers have an advantage that they have a high degree of freedomregarding placement.

The inventions disclosed in Japanese patent publication) and 2 below usean optical fiber sensor having a grating section wherein piezo elementsthat are fixed and arranged at specified locations in a structuralcomposite material, lead wires that transmit signals to the piezoelements, an optical fiber sensor attached to the structural compositematerial so that the composite material of the structural compositematerial is located between the optical fiber sensor and the piezoelements, the optical fiber sensor having a grating section to reflectlight of a specified wavelength to a core section, a light source thatshines light on the core section, and a characteristic detection unitthat detects a characteristic of the reflected light from the gratingsection, and vibrating the material by the piezo elements, detectsdamage from the change in output from the characteristics detectionunit. A spectrum analyzer that detects the frequency characteristic ofreflected light from the grating section is used as the characteristicdetection unit.

Furthermore, in the invention disclosed in Japanese Patent PublicationNo. 2005-098921, a comparison is performed with detected data of anormal structural composite material that was acquired beforehand.Alternatively, another method is disclosed in which in the frequencydistribution that is detected by the spectrum analyzer, a thresholdvalue is set for the fluctuation value from when there is no oscillationof a specified frequency, and when the detected value is equal to orless than that threshold value, it may be determined that there isdamage (paragraph 0032).

In the invention disclosed in Japanese Patent Publication No.2007-232371, two optical filters are provided in a spectrum analyzer. Itis proposed that by outputting reflected light to an arithmeticprocessing unit via the two optical filters, the spectrum analyzer willdetect a wavelength oscillation signal of the reflected light with highsensitivity. It is also proposed that the arithmetic processing unitwill calculate a value (DI value) that corresponds to the scale of thedamage of the test object based on the obtained wavelength oscillationsignal.

As a method of damage detection technology, research is being performedregarding a method in which ultrasonic waves called Lamb waves aregenerated and detected, and the occurrence of damages is diagnosed basedon the change in the detected waves. The Lamb wave is an ultrasonic wavethat propagates through a thin plate, and propagates over a longdistance with a relatively small amount of damping. Therefore, it is aform of ultrasonic wave propagation that is suitable to damagedetection. Moreover, Lamb waves have two characteristics; a multi-modecharacteristic and velocity dispersion characteristic (frequencydependence), and depending on the plate thickness and frequency, thereare plurality of modes having different speeds. Due to these complexcharacteristics, conventionally, damage detection was performed by usingonly information about a specific frequency of the Lamb waves.

SUMMARY OF THE INVENTION

Considering the above situation, the purpose of the present invention isto provide a system and method for damage diagnosis that use thedispersion characteristic of Lamb waves in order to make it possible tomeasure the mode dispersion over a broad band frequencies, make itpossible to perform quantitative evaluation of the peeling length byobtaining more useful information for damage detection than inconventional technology, and make it possible to detect and diagnosedamages with high precision and high reliability

According to a first embodiment of the present invention to achieve thepurpose described above, there is provided

a system for damage diagnosis for diagnosing a damage that occurred onor within an object, the system comprising:

an oscillator for applying a broadband ultrasonic oscillation to theobject to generate a broadband Lamb wave within the object;

an oscillation detection sensor for detecting the broadband Lamb wavefrom the object, the detected broadband Lamb wave having at least onemode of Lamb wave; and

a processing unit, being connected to the oscillator and the oscillationdetection sensor, for

(1) obtaining a time-frequency transformation data by performing atime-frequency transformation to the broadband Lamb wave detected by theoscillation detection sensor, wherein the time-frequency transformationdata indicates a propagation time of the at least one mode of Lamb wave,and the propagation time is the time for Lamb wave to propagate from theoscillator through the oscillation detection sensor, and

(2) identifying, based on the propagation time of the at least one modeof Lamb wave in the time-frequency transformation data, whether or notthe damage has occurred on or within the object, and/or identifying thesize or length of the damage that occurred on or within the object.

According to a second embodiment of the present invention to achieve thepurpose described above, there is provided

the system for damage diagnosis according to the first embodiment,wherein

the time-frequency transformation data obtained by the processing unitis a two-dimensional propagation intensity distribution data in whichfrequency is one of the two dimension and propagation time is the other.

According to a third embodiment of the present invention to achieve thepurpose described above, there is provided

the system for damage diagnosis according to the first embodiment,wherein

the at least one mode Lamb wave includes a plurality of waves havingmutually different frequencies; and

the propagation time of the at least one mode of Lamb wave is apropagation time of the maximum intensity portion of at least one of theplurality of waves.

According to a fourth embodiment of the present invention to achieve thepurpose described above, there is provided

the system for damage diagnosis according to the first embodiment,wherein

the identifying process (2) comprises a selection step for selecting theat least one mode Lamb wave among the two or more modes of Lamb waves tobe compared with the reference value.

According to a fifth embodiment of the present invention to achieve thepurpose described above, there is provided

the damage diagnostic system according to the first embodiment, whereinthe at least one mode is the S0 mode and S1 mode.

According to a sixth embodiment of the present invention to achieve thepurpose described above, there is provided

the damage diagnostic system according to the first embodiment, whereinthe at least one mode is the A1 mode, S0 mode, and S0 mode.

According to a seventh embodiment of the present invention to achievethe purpose described above, there is provided

the system for damage diagnosis according to the first embodiment,wherein

the at least one mode Lamb wave includes a plurality of waves havingmutually different frequencies; and

the processing unit, in the identifying process (2), calculatespropagation times of two of the plurality of waves, calculates a changeratio of the propagation times by means of dividing a difference of thetwo propagation times by a difference of the frequencies of the twowaves, and based on whether or not the change ratio matches thereference value, identifies whether or not damage has occurred on orwithin the object, and/or identifies the size or length of the damagethat occurred on or within the object.

According to an eighth embodiment of the present invention to achievethe purpose described above, there is provided

the damage diagnostic system according to the seventh embodiment,wherein the at least one mode is the A1 mode.

According to a ninth embodiment of the present invention to achieve thepurpose described above, there is provided

the system for damage diagnosis according to the fourth embodiment,wherein

the system comprises two oscillators, with one oscillator being attachedto one surface in the thickness direction of the object, and the otheroscillator being attached to the other surface in the thicknessdirection of the object; and

the processing unit executes an oscillation control process to controlthe oscillators, and executes the oscillation control process and theselection step under any of the conditions (a) to (c) below, where

condition (a) is such that the processing unit, in the oscillationcontrol process, controls the two oscillators so that a symmetrical modeLamb wave is generated in the object, and selects the symmetric modeLamb wave in the selection process;

condition (b) is such that the processing unit, in the oscillationcontrol process, controls the two oscillators so that a asymmetric modeLamb wave is generated in the object, and selects the asymmetric modeLamb wave in the selection process; and

condition (c) is such that the processing unit executes the processesunder conditions (a) and the processes under condition (b) at differenttimes.

According to a tenth embodiment of the present invention to achieve thepurpose described above, there is provided

the system for damage diagnosis according to the fourth embodiment,wherein

this system comprises two oscillation detection sensors, with oneoscillation detection sensor being attached to one surface in thethickness direction of the object, and the other oscillation detectionsensor being attached to the other surface in the thickness direction ofthe object; and

the processing unit executes the processes (1) and (2) under any one ofthe conditions (a) to (c) below; where

condition (a) is such that the processing unit, in the obtaining process(1), creates data in which the asymmetric mode is canceled out and thesymmetric mode is emphasized by adding the broadband Lamb waves detectedby the two oscillation detection sensors, and then the processing unitobtains time-frequency transformation data by performing thetime-frequency transformation to the created data, and in theidentifying process (2), selects a symmetric mode Lamb wave;

condition (b) is such that the processing unit, in the obtaining process(1), creates data in which the symmetric mode is canceled out and theasymmetric mode is emphasized by subtracting the broadband Lamb wavesdetected by the two oscillation detection sensors, and then theprocessing unit obtains time-frequency transformation data by performingthe time-frequency transformation to the created data, and in theidentifying process (2), selects a asymmetric mode Lamb wave; and

condition (c) is such that the processing unit executes the processesunder conditions (a) and the processes under condition (b).

According to an eleventh embodiment of the present invention to achievethe purpose described above, there is provided

a method for damage diagnosis for diagnosing a damage that occurred onor within an object, the method using

an oscillator for applying a broadband ultrasonic oscillation to theobject to generate a broadband Lamb wave within the object,

an oscillation detection sensor for detecting the broadband Lamb wavefrom the object, the detected broadband Lamb wave having at least onemode of Lamb wave, and

a processing unit being connected to the oscillator and the oscillationdetection sensor, and

the method comprises the steps of:

(1) obtaining a time-frequency transformation data by performing atime-frequency transformation to the broadband Lamb wave detected by theoscillation detection sensor, wherein the time-frequency transformationdata indicates a propagation time of the at least one mode of Lamp wave,and the propagation time is the time for Lamb wave to propagate from theoscillator through the oscillation detection sensor; and

(2) identifying, based on the propagation time of the at least one modeof Lamb wave in the time-frequency transformation data, whether or notthe damage has occurred on or within the object, and/or identifying thesize or length of damage that occurred on or within the object.

As Lamb waves, there is a Lamb wave of Symmetric mode (S mode) which hassymmetric amplitude relative to the center in the thickness direction ofthe oscillation propagation object having a plate-like shape, and a Lambwave of Asymmetric mode (A mode) which has asymmetric amplitude relativeto the center of the thickness direction of the oscillation propagationobject. Also, there are plural n dimension modes (Sn, An) which arerespectively higher dimension modes of the fundamental symmetric mode(S0) and the fundamental asymmetric mode (A0). Therefore, the waveformof the Lamb wave becomes complicated.

In the research conducted by the inventors, a method to divide thesymmetric and asymmetric modes by means of generating and detecting abroadband Lamb wave was established. As a result of analyzing each modeusing this method, it is found that S1 mode is transformed to S0 and A1modes at a peeling portion occurred between layers, those modespropagate through the peeling portion, those modes go back to S1 modeagain after having passed the peeling portion, and that S1 modepropagates through the object.

Also, it is found that A1 mode is transformed at the peeling portion toS0 mode which has a propagation speed faster than that of A1 mode, theS0 mode propagates through the peeling portion, the S0 mode goes back toA1 mode again after having passed the peeling portion, and the A1 modepropagates through the object

Thus, the change of velocity leads to the change of arrival time. Also,it is found that the arrival time of each mode shows its particularchange in accordance with the length of the peeling portion.

Therefore, by obtaining a two-dimensional propagation intensitydistribution data that is expanded 2-dimensinally according to frequencyand propagation time, and by obtaining from the data, as to a specifiedmode, a predetermined characteristic value (index which represents sizeof the damage) which shows the change of the arrival time of theobjective mode that occurs by the damage, it becomes possible todetermine as to whether or not the damage has occurred, and as to thesize of the damage.

Other features and advantages of the present invention will becomeapparent from the following detailed description, taken in conjunctionwith the accompanying drawings, which illustrate, by way of example, theprinciples of the invention.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a diagram illustrating the configuration of a damage detectionsystem of an embodiment of the present invention.

FIG. 2A is a diagram illustrating the construction of an optical fibersensor, and FIG. 2B is a line diagram illustrating the change in theindex of refraction of the grating section in the direction that lightadvances.

FIG. 3A is a diagram illustrating the construction of an optical fibersensor and the spectrum analyzer that is connected to the optical fibersensor of an embodiment of the present invention, and FIG. 3B is diagramillustrating a spectrum of the passband of eight optical filters.

FIG. 4A is a diagram of an input waveform that is inputted to an opticalfilter of an embodiment of the present invention, FIG. 4B is a spectrumof the passbands of two optical filters, and FIG. 4C is an outputwaveform of the optical filter.

FIG. 5 is a block diagram illustrating the control system of a damagedetection system of an embodiment of the present invention.

FIG. 6A is an input waveform of an FC actuator related to testing, andFIG. 6B is a Fourier spectrum of that FC actuator.

FIG. 7A is a detected wave that was detected by an FBG sensor related totesting, FIG. 7B is a Fourier spectrum of that FBG sensor, and FIG. 7Cis the wavelet transformation result.

FIG. 8 is a theoretical dispersion curve of a Lamb wave under the sameconditions as testing.

FIG. 9 is a concept diagram illustrating a mode separation method thatuses an MFC actuator.

FIG. 10 is a concept diagram illustrating a mode separation method thatuses an FBG sensor.

FIGS. 11A and 11B are diagrams illustrating mode identification resultsrelated to testing.

FIG. 12A is a concept diagram of the mode conversion behavior of a Lambwave, FIG. 12B is a theoretical dispersion curve of a Lamb wave thatpropagates inside a 2.4 mm thick plate, and FIG. 12C is a theoreticaldispersion curve of a Lamb wave that propagates inside a 1.7 mm thickplate.

FIG. 13 is a cross-sectional diagram of a test specimen related totesting.

FIG. 14 is a diagram illustrating the mode conversion behavior of the Smode found from testing.

FIG. 15 is a diagram illustrating the mode conversion behavior of the Amode found from testing.

FIG. 16 is a cross-sectional diagram of a finite-element analysis model.

FIG. 17 is a diagram illustrating the mode conversion behavior of the Smode found from finite-element analysis.

FIG. 18 is a diagram illustrating the mode conversion behavior of the Amode found from finite-element analysis.

FIGS. 19A and 19B are diagrams illustrating the difference inpropagation states, where FIG. 19A is for when the overall structure ishealthy, and FIG. 19B is for when peeling occurs.

FIG. 20 is a diagram illustrating the difference between the speed inthe A1 mode in a healthy section and in the S0 mode in a peelingsection.

FIG. 21 is a perspective diagram of a section of a measured object thatis related to detection testing of peeling between artificial layers.

FIG. 22 is a diagram illustrating a plot of the time when the maximumwavelet coefficient occurred in the A1 mode at each frequency for eachof the test specimens of different peeling lengths.

FIG. 23 is a diagram illustrating a plot of the time when the maximumwavelet coefficient occurred in the S0 and S1 modes at each frequencyfor each of the test specimens of different peeling lengths.

FIG. 24 is a graph illustrating the change in the slope of theapproximation straight line of the measurement data group for each testspecimen in the 250 to 400 kHz range in FIG. 22 with respect to thepeeling length.

FIG. 25 is a graph illustrating the change in the amount of decrease inpropagation time in the A1 mode at 300 kHz with respect to the peelinglength.

FIG. 26 is a graph illustrating the change in the amount of increase inpropagation time in the S0 an S1 modes at 350 kHz (finite-elementanalysis) and at 400 kHz (testing) with respect to the peeling length.

DETAILED DESCRIPTION OF THE INVENTION

In the following, a preferred embodiment of the present invention willbe described in detail with reference to the accompanying, exemplarydiagrams. The following is only an embodiment and does not limit thepresent invention.

[Basic Configuration]

First, the basic configuration of the damage detection system of thisembodiment is explained below.

FIG. 1 is a diagram illustrating the configuration of a damage detectionsystem 10 that detects damage in a structural composite material Z. Inthis embodiment, the structural composite material is the test objectfor which detection is performed.

In this embodiment, an MFC (Macro Fiber Composite) actuator is used asan oscillator for applying Lamb wave type ultrasonic wave oscillation toa test object. The MFC actuator has ultra thin rectangular column shapedpiezoelectric ceramic lined up in one direction and embedded in an epoxyresin, with electrodes being adhered to the upper and lower surfaces,and is capable of causing a relatively large in-plane strain to occur inone direction. Because of that characteristic, it is known that an MFCactuator can also be used as an ultrasonic oscillation element. It isalso possible to apply another kind of oscillation actuator, such aspiezoelectric elements as the oscillator.

As illustrated in FIG. 1, the damage detection system 10 of thisembodiment comprises: an MFC actuator 21 that is adhered to the surfacesection of a structural composite material Z near the location wheredamage detection of the structural composite material Z is to beperformed; an optical fiber sensor 30 as an oscillation detection sensorthat is placed near the location where damage detection of thestructural composite material Z is to be performed; a controller 41 forcontrolling the MFC actuator 21; a spectrum analyzer 42 that detects thewavelength characteristic of reflected light that is obtained from theoptical fiber sensor 30; and an arithmetic processing unit 50 thatperforms arithmetic processing of output values from the spectrumanalyzer 42. The power source 43 for the spectrum analyzer 42 is alsoillustrated in the figure.

When a driving voltage is applied from the outside, the MFC actuator 21causes a relatively large in-plane strain to occur in one direction inthat plane. Using this, the controller 41 applies a driving voltage tothe MFC actuator 21 in order to apply an instantaneous oscillation tothe structural composite material Z.

The optical fiber sensor 30 is an FBG (Fiber Bragg Grating) opticalfiber sensor, and as illustrated in FIG. 2A is made from an opticalfiber 34 having a grating section 33 located inside the core section 32that reflects light of a certain wavelength.

One of the end sections of the optical fiber 34 is connected to thespectrum analyzer 42, and light covering a specified range of wavelengthbands is irradiated from the light source of that spectrum analyzer 42and enters into the core section 32. The light that enters from thespectrum analyzer 42 propagates through the core section 32 and onlysome of the light wavelengths are reflected by the grating section 33.

FIG. 2B is a line diagram illustrating change in the refractive index inthe advancement direction of the light through the core section 32, andin the figure, the range L illustrates the refractive index in thegrating section 33.

As illustrated in the figure, the grating section 33 is constructed suchthat the refractive index of the core section 32 changes at a fixedcycle. The grating section 33 selectively reflects only light of certainwavelength at the boundary sections where the refractive index changes.

Here, the change in the wavelength ΔλB of the reflected light from theFBG optical fiber sensor is represented by equation (1) below where n isthe effective refractive index of the core, Λ is the grating interval,P11 and P12 are Pockels coefficients, ν is the Poisson's ratio, ε is theapplied strain, α is the temperature coefficient of the fiber materialand ΔT is the change in temperature (Alan D. Kersey, “Fiber GratingSensors”, JOURNAL OF LIGHTWAVE TECHNOLOGY, Vol. 15, No. 8, 1997).

$\begin{matrix}{\mspace{79mu} \left\lbrack {{Formula}\mspace{14mu} 1} \right\rbrack} & \; \\{{\Delta\lambda}_{B} = {2n\; {\Lambda\left( {{\left\{ {1 - {\left( \frac{n^{2}}{2} \right)\left\lbrack {P_{12} - {v\left( {P_{11} + P_{12}} \right)}} \right\rbrack}} \right\} ɛ} + {\left\lbrack {\alpha + \frac{\left( \frac{n}{T} \right)}{n}} \right\rbrack \Delta \; t}} \right)}}} & (1)\end{matrix}$

Therefore, when oscillation occurs in the grating section 33, the amountof strain ε in the grating section 33 changes, and as a result, thewavelength of the reflected light fluctuates according to the amount ofstrain ε. As long at the oscillation is transmitted in a good mannerfrom the oscillation source, the grating section 33 generates a largestrain, and the amount of change in the wavelength ΔλB fluctuates a lot,however when the oscillation is not transmitted in a good manner fromthe oscillation source, the grating section 33 generates small strain,and the amount of change in the wavelength ΔλB fluctuates only a little.

The MFC causes strain orthogonal to the axial direction of the fibrouspiezoelectric element to occur, and the FBG detects strain in the axialdirection that occurred in the fibrous optical fiber. These elementshave a wide frequency characteristic without having a resonantfrequency, and because these elements have strong directivity, thepropagation path is distinct. Using these two characteristics, themeasurement system of this embodiment is able to allow propagation ofbroadband Lamb waves having directivity. The FBG and MFC are bothcompact and lightweight, are flexible and have a high failure strain, socan be integrated with a laminated plate, they will not fail even underlarge strain, so have high reliability, and having such characteristicsare suitable for use in structural health monitoring.

FIG. 3A illustrates an example of the construction of the optical fibersensors and the spectrum analyzer that is connected to the sensors. Asillustrated in FIG. 3A, the spectrum analyzer 42 comprises a lightsource 61, an optical circulator 62, an AWG module 63 and aphotoelectric converter 60. In this embodiment, an optical fiber 34, inwhich four optical fiber sensors 30 a to 30 d having different reflectedwavelengths are arranged in series, is connected to the spectrumanalyzer 42. The minimum structure is the optical sensors 30.

The light source 61 is a broadband light source that includes all of theoscillation areas of the reflected wavelengths of the optical fibersensors 30 a to 30 d. This is so that even when there is oscillation atthe reflected wavelengths of the optical sensors 30 a to 30 d due to aLamb wave, it is always possible to obtain the fully reflected light.

The optical circulator 62 causes light from the light source 62 toadvance toward the optical fiber sensors 30 a to 30 d, and directs thereflected light from the optical fiber sensors 30 a to 30 d to theoptical fiber 69. The reflected light that is guided to the opticalfiber 69 is led to the input port P0 of the AWG module 63.

The AWG module 63 has an AWG substrate 64. A monolithic integratedlightwave circuit is formed on the AWG substrate 64. The lightwavecircuit on the AWG substrate 64 has input/output slab waveguides 65, 66,an array waveguide 67 and an output waveguide 68, and forms eightoptical filters having different passbands that are connected inparallel to the input port P0. The lightwave circuit on the AWGsubstrate 64 divides the wavelength multiplexed input light intodifferent wavelengths by passing the light through the eight opticalfilters, and outputs that light in parallel to eight output ports P1 toP8. However, the actual number of output ports is not limited to eight.

Each of the passbands of the optical filters that corresponds to theeight output ports P1 to P8 are illustrated in the spectrum in FIG. 3B.For example, in FIG. 3B, the reflected light that corresponds to theportion where the reflected light input distribution 70 of the opticalfiber sensor 3 b that has a center reflected wavelength of λ2 overlapspassband 71 is allowed to pass through one of the optical filters and isoutputted to the output port P3, and at the same time, the reflectedlight that corresponds to the portion that overlaps passband 72 isallowed to pass through another optical filter and is outputted to theoutput port P4. Similarly, output ports P1 and P2 correspond to theoptical fiber sensor 30 a having a center reflected wavelength of λ1,output ports P5 and P6 correspond to the optical fiber sensor 30 chaving a center reflected wavelength of λ3, and output ports P7 and P8correspond to the optical fiber sensor 30 d having a center reflectedwavelength of λ4, and dividing the wavelengths is possible in the sameway. As described above the minimum structure is one optical fibersensor, and in this case two optical filters are sufficient.

On behalf of all, the processing that is performed on the reflectedlight from one optical fiber sensor 30 will be explained with referenceto FIGA. 4A and 4B.

As illustrated in FIG. 4B, an input distribution 73T of the reflectedlight from the optical fiber sensor 30 appears. When oscillation isapplied by the MFC actuator 21, a Lamb wave, having the MFC actuator asthe oscillation source, propagates through the structural compositematerial Z, and the optical fiber sensor 30 causes oscillation at thewavelength of the outputted reflected light according to the Lamb wavethat is transmitted from the structural composite material Z. Theoscillation at this wavelength is graphically illustrated by input wave73W in FIG. 4A.

Due to the oscillation at this wavelength, the reflected light inputdistribution 73T illustrated in FIG. 4B alternately shifts upward anddownward a little, so there is a repeated increase and decrease in thewavelength value.

At such a wavelength oscillation, 73C in the figure is the oscillationcenter having the center wavelength of the reflected light inputdistribution 73T. On the other hand, the center wavelength 75C of thepassband 75T of the optical filter is fixed in the area above theoscillation center 73C.

Moreover, the center wavelength 75C and center wavelength 74C are fixedat positions that are separated by at least the amplitude of thewavelength oscillation of the reflected light from the oscillationcenter 73C.

Furthermore, when the reflected light input distribution 73T is still,the slope 75T-1 on the lower side of the upper passband 75T crosses theslope 73-T on the upper side of the reflected light input distribution73T, and the upper passband 75T and the reflected light inputdistribution 73T overlap with a width that is equal to or greater thanthe amplitude of the wavelength oscillation.

Similarly, when the reflected light input distribution is still, theslope 74T-1 on the upper side of the lower passband 74T crosses theslope 73T-2 on the lower side of the reflected input light distribution73T, and the lower passband 74T and reflected light input distribution73T overlap with a width that is equal to or greater than the amplitudeof the wavelength oscillation.

By fixing the passband 75T and passband 74T with a position relationshipwith respect to the reflected light input distribution 73T as describedabove, it is possible to detect wavelength oscillation of the reflectedlight with high sensitivity.

The upper optical filter allows the reflected light corresponding to theportion where the reflected light input distribution 73T overlaps thepassband 75T to pass, and outputs the reflected light. Similarly, thelower optical filter allows the reflected light corresponding to theportion where the reflected light input distribution 73T overlaps thepassband 74T to pass, and outputs the reflected light.

Therefore, when the value of the wavelength of the reflected lightincreases and the reflected light input distribution 73T shifts upward,the output value of the upper optical filter having passband 75Tincreases, and the output value of the lower optical filter havingpassband 74T decreases. However, when the value of the wavelength of thereflected light decreases and the reflected light input distribution 73Tshifts downward, the output value of the upper optical filter havingpassband 75T decreases, and the output value of the lower optical filterhaving passband 74T increases.

Consequently, when the change in the center wavelength of the reflectedlight oscillates due to the input wave 73W illustrated in FIG. 4A, theoutput value of the upper filter having passband 75T generates theoutput wave illustrated in FIG. 4C, and the lower optical filter havingpassband 74T generates the output wave 74W illustrated in FIG. 4C. Asillustrated in FIG. 4C, the output wave 74W and output wave 75W haveopposite phase wave motion.

According to the theory above, the spectrum analyzer 42 illustrated inFIG. 3 outputs lightwaves to the eight output ports P1 to P8 whenoscillated, and these lightwaves are changed to electrical signals bythe photoelectric converter 60 and outputted to the outside. The outputfrom the spectrum analyzer 42 undergoes A/D conversion by an interface(not illustrated in the figure) and inputted to the arithmeticprocessing unit 50.

As illustrated in FIG. 5, the arithmetic processing unit 50 comprises aCPU 51 that performs arithmetic processing according to a program, ROM52 that stores programs for performing various processing and control,RAM 53 that becomes a work area that temporarily stores data and thelike for various processing, an interface 54 that makes it possible totransmit data to or receive data from the control unit 41, an interface55 that inputs data from the spectrum analyzer 42, an image outputinterface 57 that converts the display data of the processing results toan image signal having a format that is suitable to the display 56, andoutputs that signal to the display 56, and a data bus 58 that is usedfor transmitting various instructions or data between all of thecomponents above.

The damage detection system 10, together with applying oscillation to astructural composite material Z, which is the object of damagedetection, by way of the MFC actuator that is placed on the structuralcomposite material, detects whether or not damage has occurred near theoptical fiber sensors 30 according to the propagation state of theoscillation wave that is detected by the optical fiber sensors 30. Inorder to accomplish that, the arithmetic processing unit 50 executesvarious functions explained below by the CPU 51 using the RAM 53 toperform the processing of the various programs stored in the ROM 52.

The CPU 51, according to the programs stored in the ROM 52, controls theoperation of the control unit 41 so that a driving voltage is applied tothe MFC actuator 21. When there is a plurality of MFC actuators 21, anyone of the actuators can be selected as the MFC actuator 21, however,when used as an oscillation source, for example, it is preferred that anMFC actuator be selected such that there is a portion between theoptical fiber sensors 30 and the grating section 33 where damage to thestructural composite material Z occurs easily.

The CPU 51, according to a program stored in the ROM 52, performsprocessing of applying a driving voltage, acquiring output wave datathat is outputted in parallel from the spectrum analyzer 42 during thefixed period of oscillation caused by the MFC actuator 21, and storingthe acquired data in the RAM 53.

The CPU 51, issues control instructions, and by way of the MFC actuator21 applies the ultrasonic oscillation of a Lamb wave to the structuralcomposite material Z, and quantifies and obtains the difference signalof the output wave 74W and the output wave 75W from the optical filterthat is obtained during oscillation. For example, the difference signalf(t) illustrated in FIG. 7A is obtained.

The CPU 51 also performs wavelet conversion of the f(t) data accordingto Equation (2). As a result, the f(t) data is converted to propagationintensity distribution data that is expanded 2-dimensionally accordingto frequency and propagation time. This data corresponds to thepropagation intensity distribution of the Lamb wave to the optical fibersensors 30, and when represented graphically becomes as illustrated inFIG. 7C.

[Formula 2]

F(a,b)=∫_(−∞) ^(∞) f(t)ω*_(a,b)(t)dt  (2)

[Damage Detection Operation]

Using the basic configuration explained above, and further asillustrated in FIG. 19 or FIG. 21, MFC actuators 21, 21 and opticalfiber sensors 30, 30 are placed at the same positions on the top andbottom of the structural composite material Z, and the damage detectionoperation described below is executed.

The CPU 51, by causing the top and bottom MFC actuators 21, 21 togenerate an oscillating wave in the same phase, applies oscillation injust the symmetrical mode to the structural composite material Z, thenperforms wavelet conversion of the f(t) data as described above andobtains 2-dimensional expanded data according to the frequency andpropagation time of just the S mode as illustrated in FIG. 11A. Afterthat, the CPU 15, based on the theoretical dispersion curve illustratedin FIG. 8, specifies a mode, such as the S0 mode, S1 mode, S2 mode andthe like, and calculates the propagation time where the maximum waveletcoefficient value occurs for each frequency in the specified mode. Forexample, when specified modes are the S0 mode and S1 mode, asillustrated in FIG. 23, the relationship between frequency and time atwhich the maximum wavelet coefficient value occurs is specified. This isone characteristic value and one measurement result that is extractedfrom the 2-dimensional expanded data. The CPU 51 displays this on thedisplay 56 as illustrated in FIG. 23.

The CPU 51 displays the measurement results for a test object for whichthe damage state is unknown in the same way as and together with themeasurement results for a structure for which the damage state is known.The tester references this, and through comparison, can estimate whetheror not there is damage, and to what extent damage has occurred.

Alternatively, the propagation time in the S0 mode and the S1 modeincreases as the length of the lamination peeling increases, so, asillustrated in FIG. 26, the CPU 51 displays the amount of increasedpropagation time with respect to the case when there is no damage. Thetester references this and can estimate whether or not there is damage,and to what extent damage has occurred.

The CPU 51 further advances, and based on the multiple measurementresults stored in the ROM 52 for a structure for which the damage stateis known, and the measurement results for a test object for which thedamage state is not known, performs estimation of the extent of thedamage that has occurred in the test object, and can display thoseresults on the display 56.

In order to acquire data for the symmetrical mode (S mode), instead ofthe method above, by adding the output values of the top and bottomoptical fiber sensors 30, 30, it is possible to obtain 2-dimensionaldata (propagation intensity distribution data) of which the asymmetricalmode is cancelled and the symmetrical mode is emphasized.

The CPU 51, by causing the top and bottom MFC actuators 21, 21 togenerate an oscillating wave having opposite phase, applies just theasymmetrical mode to the structural composite material Z, performswavelet conversion of the f(t) data as described above, and obtains2-dimensional expanded data according to the frequency and propagationtime of just the A mode as illustrated in FIG. 11B. After that, the CPU51 specifies a mode such as the A0 mode and A1 mode, and calculates thepropagation time at which the maximum wavelet coefficient value occursfor each frequency of the specified mode. For example, when thespecified mode is the A1 mode, the relationship between the frequencyand the propagation time at which the maximum wavelet coefficient valueoccurs as illustrated in FIG. 22 is specified. This is onecharacteristic value and one measurement result that is extracted fromthe 2-dimensional expanded data.

The CPU 51 displays this on the display 56 as illustrated in FIG. 22.The CPU 51 displays the measurement results for a test object for whichthe damage state is not know in the same way as and together with themeasurement results for a structure for which the damage state is known.The tester references this, and by making a comparison, is able toestimate whether or not there is damage, and to what extent damage hasoccurred.

Alternatively, the propagation time in the A1 mode is reduced due toconversion to the S0 mode, which has a faster propagation time than theA1 mode in the damaged area, so the CPU 51 displays the amount of thereduction in propagation time with respect to the case in which there isnot damage. The tester references this, and is able to estimate whetheror not there is damage, and to what extent damage has occurred.

Moreover, the CPU 51 calculates the rate of change in the frequency withrespect to the propagation time for the A1 mode. The approximationstraight line of the measurement data sets of each test specimen in the250 to 450 kHz range is calculated, and the rate of change correspondsto the slope of the approximation straight line. This also is onecharacteristic value and one measurement value that is extracted from2-dimensional expanded data. The CPU 51 displays this rate of change(slope) numerically and in a graph as illustrated in FIG. 4. Here also,the CPU 51 displays measurement results for the test object for whichthe state of damage is unknown in the same way as and together with themeasurement results for a structure for which the state of damage isknown. The tester references this, and by making a comparison, is ableto estimate whether or not there is damage, and to what extent damagehas occurred.

Advancing further, based on the multiple measurement results stored inROM 52 for a structure for which the damage state is known andmeasurement results for a test object for which the damage state isunknown, the CPU 51 performs estimation of the extent of data to thetest object, and can display the results on the display 56. The basicdata for estimation calculation is the amount of increase in propagationtime in the S0 mode and S1 mode described above, and the amount ofdecrease and rate of change (slope) in the propagation time in the A1mode.

In order to acquire data in the asymmetrical mode (A mode), instead ofthe method above, it is possible to obtain 2-dimensional expanded data(propagation intensity distribution data), in which the symmetrical modeis canceled out and the asymmetrical mode is emphasized, by subtractingthe output values from the top and bottom optical fiber sensors 30, 30.

In the embodiment described above, the difference signal between theoutput values of two optical filters was taken to be the basic data forwavelet conversion, however, the invention is not limited to this, andthe output value of one optical filter could be taken to be the basicdata for wavelet conversion.

Moreover, in the embodiment above, the maximum peak value of the waveletcoefficient for a specified mode was calculated, however, the value ofany parameter may be used as long as the parameter is suitable for usein comparing the acquired Lamb wave in specified modes.

Furthermore, in the embodiment described above, wavelet conversion wasapplied as the method of conversion for 2-dimensionally expanding thedetected values from the optical sensors according to frequency andpropagation time, however, the present invention is not limited to this,and it is also possible to apply other conversion methods such asshort-time Fourier transformation, chirplet transformation, Wignertransformation, Stockwell transformation, or a combination of any two ormore of said transformations.

[Verification Testing and Analysis]

Next, as a reference when explaining the theory of the present inventionand when embodying the present invention, a description of verificationperformed through testing and analysis is given below.

1. MODE IDENTIFICATION METHOD (MODE SEPARATION METHOD)

First, measurement was performed for a quasi-isotropic CFRP laminatedplate (T700S/2500, Toray Industries Inc., [45/0/−45]3s, thickness: 3.4mm). The MFC (M-2814-P2, Smart Material Co., Ltd.) had a length of 6 mm,width of 14 mm and thickness of 0.3 mm, and the FBG sensor (Fujikura,Ltd.) had a sensor length of 1.5 mm, and diameter with polyimide coatingof 150 μm. Both were adhered to the surface of the CFRP laminated plate,being separated by 100 mm, and measurement was performed. Both wereadhered to the surface using Aron Alpha (Konishi Co., Ltd.), which is aCyanoacrylate type adhesive. A broadband signal with a hamming window inthe first cycle of an fc=400 kHz sine wave as illustrated in FIG. 6 wasused as the input signal to the MFC. In order to remove the noise fromthe received oscillation waveform of the Lamb wave, which is generatedby the MFC, propagates through the laminated plate and is received by anFBG sensor, averaging was performed by waveforms measured 32,768 times.After that, signal analysis of the obtained received waveform wasperformed, and the mode dispersion characteristics that were included inthe received oscillation wave were expressed in the time-frequencydomain. A complex Morlet function was used as the window function insignal analysis, and 1D complex continuous wavelet analysis wasperformed. The waveform of the wave received by the FBG sensor, theFourier spectrum of that waveform, and the wavelet conversion resultsare illustrated in FIG. 7. As a result, it could be confirmed that awave component covering a broadband was received without a large peakappearing at the specified frequency. Moreover, from the waveletconversion results, a plurality of modes having different speeds andfrequencies were observed and found to have mode dispersion. Next, thetheoretical dispersion curve for identifying each mode that appears inthe received oscillation wave is derived.

FIG. 8 illustrates the theoretical dispersion curve that was derived atthe arrival time at a propagation distance of 100 mm in a 3.4 mm CFRPlaminated plate that is the same as used in the testing above. In thisdispersion curve, the arrival time of high-dimension modes suddenlybecomes late, and where the frequency becomes infinitely large is calledthe cutoff frequency. By comparing this theoretical dispersion curvewith the wavelet conversion results of the received oscillation waveformabove, it can be seen that the mode dispersion coincides well betweenboth. However, in the frequency domain of 300 kHz and greater where aplurality of modes overlap, it is difficult to identify the mode, so inorder to perform accurate mode identification, it is necessary toseparate these overlapping modes.

Therefore, a method of adhering both an MFC and FBG sensor at the samelocations on the top and bottom surface of the laminated plate was usedas a method for separating these modes. As illustrated in FIG. 9, an MFCis adhered at the same location on the top and bottom surface, and whenthe MFC generate waves that are in phase, it is possible to performoscillation in just the symmetrical mode. On the other hand, when wavesare generated having opposite phase, it is possible to performoscillation in just the asymmetrical mode.

As illustrated in FIG. 10, an FBG sensor is adhered to the same positionon both the top and bottom surface, and by taking the sum of thereceived oscillation waveform of the top and bottom of the plate, it ispossible to separate the symmetrical modes, and by taking thedifference, it is possible to separate the asymmetrical modes.

The result of using these two methods to separate the S (symmetrical)modes and A (asymmetrical) modes, perform wavelet conversion, and thenperform comparison with the theoretical dispersion curve above isillustrated in FIG. 11. As a result, by separating the modes,overlapping of a plurality of modes is eliminated, and the modes couldbe identified accurately. It was also confirmed that in the receivedoscillation waveform there were the A0, S0, A1, S1 and S2 modes.

From the results above, it is possible to identify each mode included ina received Lamb wave by using the mode separation method above.

2. CAUSE OF CHANGE IN THE PROPAGATION TIME IN A SPECIFIED MODE (MODECONVERSION BEHAVIOR IN A SECTION OF PEELING BETWEEN LAYERS)

In the previous section, identification of each mode was performed, andit became possible to understand the mode dispersion included in themeasurement results. Next, the mode conversion behavior that occurs dueto changes in the mode dispersion is clarified through testing andanalysis.

(1) Mode Conversion Due to Changes in Sheet Thickness at Peeling Areas

The propagation speed of a Lamb wave depends on the product of thefrequency and plate thickness, so as the plate thickness changes, themode dispersion of a Lamb wave also changes. Therefore, as illustratedin FIGS. 12A to 12C, when peeling occurs between layers inside alaminated plate, the plate thickness of the propagation path at the areaof peeling is less than in a healthy section, so the mode dispersion isdifferent in healthy sections and peeling sections. Due to this changein mode dispersion, it is thought that mode conversion occurs in theLamb wave that propagated through a healthy section, and propagatesthrough a peeling section in a different mode form than in a healthysection.

For example, in a laminated plate having a plate thickness of 3.4 mm,there are three modes, A0, S0 and A1 modes, as the propagation form of aLamb wave having a frequency of 300 kHz, however, when peeling occursbetween layers in the center of the laminated plate, the plate thicknessin the peeling section changes to 1.7 mm and there are only twopropagation forms, the A0 mode and S0 mode.

Therefore, a Lamb wave that propagated though a healthy section as theA1 mode, undergoes mode conversion in the peeling section, andpropagates as the A0 and S0 modes. However, which mode the wave willpropagate by through the peeling section cannot be found from thetheoretical dispersion curve. Therefore, the actual mode conversionbehavior that occurs in peeling sections between layers is made clear byperforming testing and finite-element analysis.

(2) Experiment

In order to make clear the actual mode conversion behavior that occursat the beginning and ending of a peeling section between layers, aquasi-isotropic CFRP laminated plate (T700S/2500, Toray Industries Inc.,[45/0/−45]3s, thickness: 3.4 mm) was used to simulate the case in whichpeeling between layers occurs in the center in the thickness directionof the plate. Mode identification of a received Lamb wave is performedby mode separation, so in order to measure the mode dispersion in apeeling section it is necessary to adhere an FBG sensor to the interiorsurface of the simulated peeling between layers. Therefore, two 1.7 mmthick CFRP laminated plates were prepared, and after an FBG sensor wasadhered to one, and in order that the surface to which the FBG sensorwas adhered was inside, an epoxy type adhesive, Araldite Standard(Huntsman Advanced Materials, Inc.) was applied in a 60 mm range fromone end of the plate. The two CFRP laminated plates, in order tosimulate a laminated structure [45/0/−5/90]3s, were made with alaminated structure [45/0/−45/90]3, and were symmetrically adhered tothe mounting surface. The dimensions of the test specimen areillustrated in FIG. 13. The width of the plate is 90 mm.

The MFC (M-2814-P2) that was used had a length of 6 mm, a width of 14 mmand a thickness of 0.3 mm, and one was adhered to both the top andbottom surface of the laminated plate. FBG sensors were adhered to thetop and bottom surface of the laminated plate at two points; a distance30 mm from the tip end of the MFC where the plate thickness was 3.4 mm(healthy section), and at a distance 70 mm where the plate thickness was1.7 mm (peeling section), and these sensors received the Lamb wave. TheFBG sensors (Fujikura Ltd.) that were used in testing had a sensorlength 1.5 mm, and diameter with polyimide coating of 150 μm. Aron Alpha(Konishi Co., Ltd.) was used for adhering the elements. The input signalwas a fc=400 kHz sine wave with a hamming window in one cycle, and inorder to remove noise from the received oscillation waveform, averagingwas performed by waveforms measured 32,768 times. The mode conversionbehavior of the S mode that was found by performing oscillation in justthe S (symmetrical) mode using the MFC on both the top and bottomsurfaces is illustrated in FIG. 14, and the mode conversion behavior ofthe A mode that was found by performing oscillation in just the A(asymmetrical) mode is illustrated in FIG. 15.

From the results in FIG. 14, in the case of generating oscillation inonly the S mode, only the S0 mode and S1 mode were observed in thehealthy section. From the theoretical dispersion curve in the case ofthe 1.7 mm plate thickness illustrated in FIG. 12C, it is seen that inthe peeling section, the S1 mode only existed at 800 kHz or greater, soit is thought that in the healthy section, the S1 mode undergoes modeconversion in the peeling section and the wave propagates as anothermode. Therefore, observing the modes that exist in the peeling section,two modes, the S0 mode and A1 mode, were observed. From this result, atthe start of the peeling section, it was confirmed that “S1 mode→S0mode→A1 mode” mode conversion occurred.

From the results in FIG. 15, when oscillation was generated in only theA mode, only the A0 mode and A1 mode were observed in the healthysection. From the theoretical dispersion curve in the case of a 1.7 mmplate thickness illustrated in FIG. 12C, it was seen that in the peelingsection, the A1 mode existed at only 500 kHz or greater, so it isthought that the A1 mode that was observed in the healthy sectionundergoes mode conversion in the peeling section and that the wavepropagates as another mode. Therefore, observing the modes that exist inthe peeling section, two modes, the S0 mode and A1 mode are observed(the arrival time of the A0 mode is late, so is not considered to be anobject of mode conversion). In this peeling section, it is thought thatthe observed A1 mode does not undergo mode conversion, but that at 500kHz or greater, the A1 mode propagates as is. Therefore, from thisresult, at the start of the peeling section, it was confirmed that “A1mode→S0 mode” mode conversion occurred.

(3) Verification by Finite-Element Analysis

In order to verify the mode conversion behavior found from observationin (2) above, 2D finite-element analysis was performed. Thefinite-element model and dimensions are illustrated in FIG. 16. AnLS-DYNA 971 was used for the model construction and analysis. Theelements used for the analysis model were 2D shell elements (planestrain). The mesh size was 0.125 mm, which was sufficiently small enoughto be able to calculate high-frequency waves with a short wavelength.Node bonding is performed for the contact sections between the MFC andCFRP laminated plate, and as in testing, a sine wave having a frequencyof 400 kHz and a hamming winding in 1 cycle was used as the inputwaveform to the MFC. With the LS-DYNA it is not possible to calculatethe piezoelectric effect, so the piezoelectric effect was applied as thecoefficient of thermal expansion in the direction of expansion of theMFC and simulated. Under the conditions described above, the timehistory of the strain in the x direction was calculated at the threeoscillation receiving points illustrated in FIG. 16 (healthy section: 20mm propagation distance 20, 3.4 mm plate thickness; peeling section: 60mm propagation distance, 1.7 mm plate thickness; and healthy section(after passing the peeling section): 100 mm propagation distance, 3.4 mmplate thickness), and this was taken to be the received oscillationwaveform. The mode conversion behavior in the S mode that was found byperforming oscillation in only the S (symmetrical) mode using both thetop and bottom MFC is illustrated in FIG. 17, and the mode conversionbehavior in the A mode that was found by performing oscillation in onlythe A (asymmetrical) mode is illustrated in FIG. 18.

From the results in FIG. 17, at the start of peeling between layers, itwas confirmed that the same “S1 mode S0 mode A1 mode” mode conversion asin the testing occurred. Moreover, in the healthy section after passingthe peeling between layers, the same dispersion as in the healthysection before passing the peeling was observed, and the S0 mode and S1mode were observed. When this S1 mode propagated through the peelingsection and returned to the healthy section, it is thought that the S0mode and A1 mode of the peeling were converted again to the S1 mode inthe healthy section.

Next, from the results in FIG. 18, it was confirmed that at the start ofthe peeling between layers, there was the same “A1 mode→S0 mode” modeconversion as in testing. Moreover, in the healthy section after passingthe peeling between layers, the same dispersion as in the healthysection before passing the peeling was observed, and the A0 mode and A1mode were observed.

When this A1 mode propagates through the peeling section and returns tothe healthy section, it is thought that the S0 mode in the peelingsection undergoes mode conversion and is converted again to the A1 modein the healthy section.

The above indicates the validity of the mode conversion behavior foundthrough testing, and further makes clear the mode conversion behaviorthat occurs after the peeling between layers ends. As a result, it wasconfirmed that when passing through the peeling section between layers,the following two mode conversions exist.

-   -   “S1 mode→S0 mode, A1 mode→S1 mode”    -   “A1 mode→S0 mode A1 mode”

Due to this kind of mode conversion behavior, the mode duringpropagation through a peeling section and the mode during propagationthough a healthy section differ. For example, as illustrated in FIG. 19,in the “A1 mode S0 mode A1 mode” mode conversion, in the healthysections, propagation in all propagation paths is in the A1 mode,however, when peeling occurs, propagation through that area is in the S0mode. Here, the propagation speeds in the A1 mode in healthy sections(3.4 mm plate thickness) and in the S0 mode in peeling section (1.7 mmplate thickness) differ, with the speed of the S0 mode being faster thanthat of the A1 mode. Therefore, the arrival time of oscillation in theA1 mode that is received by the FBG sensor is earlier when peeling hasoccurred than when healthy. This change in the arrival time occurs dueto the difference in propagation speeds of a mode propagating thoughhealthy sections and a mode propagating through peeling sections, andthe length of the peeling. Therefore, by taking this difference as anindex, it is possible to detect peeling between layers, and toquantitatively evaluate the peeling length.

3. VERIFICATION TESTING AND ANALYSIS OF DETECTION OF ARTIFICIAL PEELINGBETWEEN LAYERS

(1) Verification Testing

The effectiveness of the present invention is illustrated by verifyingthrough testing whether or not there is actually a change in arrivaltime of a wave after passing through a peeling section.

Therefore, three kinds of laminated plates were made in which, whileforming an isotropic laminated plate such as a quasi-isotropic CFRPlaminated plate, peeling, having peeling lengths L=20, 40 and 60 mm, wasartificially introduced between layers in the center in the platethickness direction by embedding two layers of 50 μm thick Teflon(registered trademark) film between adjacent 90° layers in the center inthe plate thickness direction. A broadband Lamb wave was caused topropagate such that it passed through these peeling areas, and thereceived oscillation waveform was measured. The testing configuration isillustrated in FIG. 21. An MFC and FBG sensor were adhered to the samelocations on the top and bottom surfaces of the plate, and modeseparation was performed in the same way as was performed in the case ofclarifying the mode conversion behavior in the previous section.

Using this testing configuration, detection of peeling betweenartificial layers was tested using a laminated plate in which artificialpeeling, having lengths L=20, 40 and 60 mm, was introduced. The resultsof this testing were compared with the results when a healthy laminatedplate (L=0) was measured, and the change in the arrival time wasevaluated.

In order to do this, after the received oscillation waveform underwentwavelet conversion, the maximum value of the wavelet coefficients foreach frequency was extracted. When there was peeling between layers, theamount of change in the time of this maximum wavelet coefficient fromthe healthy state corresponds to the change in arrival time.

When oscillation was generated in the A mode using the MFC on both thetop and bottom, the “time at which the maximum wavelet coefficientappeared for each frequency” in the A mode that was measured by the FBGsensors is illustrated in FIG. 22 for the 200 to 700 kHz A1 mode inwhich relatively large change occurred in the arrival time for the casesof L=0, 20, 40 and 60 mm.

Next, when oscillation was generated in the S mode using the MFC on boththe top and bottom, the “time at which the maximum wavelet coefficientappeared for each frequency” in the S mode that was measured by the FBGsensors is illustrated in FIG. 23 for the 400 to 600 kHz S0 and S1 modesin which relatively large change occurred in the arrival time for thecases of L=0, 20, 40 and 60 mm.

From FIG. 22 it is observed that as the peeling length becomes longer,the arrival time of the A1 mode becomes earlier. It is also observedthat there is change in the slope of the mode dispersion in the 200 to500 kHz frequency range. As illustrated in FIG. 20, this means that thecloser the frequency is to the cutoff frequency of the A1 mode(frequency become low), the greater the difference between thepropagation speed of the S0 mode and A1 mode becomes.

Moreover, from FIG. 23 it is observed that as the peeling length becomeslong, the arrival time of the S0 and S1 modes becomes later.

The results above, show that there is indeed change in the arrival timewhen peeling between layers occurs, and that the present invention iseffective.

(2) Verification Through Finite-Element Analysis

In section 2.(3) above, the peeling length of a 2D finite-elementanalysis model was changed as L=20, 40 and 60 mm, and analysis wasperformed using the same testing configuration as in the testing above.After that, as in the testing, the maximum amplitude was found for theA1 mode and S0 and S1 modes, and in observing the change in the arrivaltime, the results of the testing (FIG. 22, FIG. 23) coincide and thesame change was observed.

(3) Quantitative Evaluation of the Peeling Length

Furthermore, using the change in the arrival time that was observed fromtest results in (1) above and from the analysis results in (2) above, orthe slope of the mode dispersion as an index, it is shown that it ispossible to quantitatively evaluate the peeling length.

A linearly approximated straight line is calculated from a plot ofmaximum amplitude values in the frequency ranges where change occurredin the arrival time, and using that approximated straight line, thefollowing indices were found. The indices were found from test resultsand analysis results. The results of plotting the indices for eachpeeling length are illustrated in FIG. 24, FIG. 25 and FIG. 26.

FIG. 24 illustrates the slope of the mode dispersion of the 250 to 400kHz A1 mode, FIG. 25 illustrates the amount of decrease in the arrivaltime of the A1 mode at 300 kHz, and FIG. 26 illustrates the amount ofincrease in the arrival time of the S0 and S1 modes at 400 kHz (analysiswas at 350 kHz).

From the results in FIG. 24, it is observed that as the peeling lengthbecomes longer, the slope of the mode dispersion becomes smaller. Also,from the results of FIG. 25 and FIG. 26, it is observed that as thepeeling length becomes larger, the amount of decrease in the arrivaltime of the A1 mode, and the amount of increase in the arrival time ofthe S0 and S1 modes becomes greater. These indices change nearlyproportional to the peeling length. Therefore, it is possible to usethese indices to quantitatively evaluate the peeling length.

4. CONCLUSION

As described above, first, identification was performed of each mode ofa broadband Lamb wave that is measured in a broadband ultrasonictransmission system. A method of separating symmetrical/asymmetricalmodes is proposed as a method for doing this, and it was shown that modeidentification is possible by using this separation method.

Next, the mode conversion behavior in peeling sections between layerswas clarified through testing and analysis, and it was confirmed thatthere are two types of mode conversion behavior, “S1 mode→S0 mode, A1mode→S1 mode” and “A1 mode→S0 mode→A1 mode”.

After that, the validity of the peeling detection method of the presentinvention, which uses the change in speed of a Lamb wave due to modeconversion, was verified through testing and analysis. As a result, itwas confirmed that the change in speed in the peeling sections wasobserved as the change in arrival time.

Finally, it was shown that the peeling length could be quantitativelyevaluated using the slope of the mode dispersion in the A1 mode, theamount of decrease in the arrival time of the A1 mode and the increasein the arrival time of the S0 and S1 modes as indices.

It is to be understood that the above-described embodiments areillustrative of only a few of the many possible specific embodimentswhich can represent applications of the principles of the invention.Numerous and varied other arrangements can be readily devised by thoseskilled in the art without departing from the spirit and scope of theinvention.

1. A system for damage diagnosis for diagnosing a damage that occurredon or within an object, the system comprising: an oscillator forapplying a broadband ultrasonic oscillation to the object to generate abroadband Lamb wave within the object; an oscillation detection sensorfor detecting the broadband Lamb wave from the object, the detectedbroadband Lamb wave including at least one mode of Lamb wave; and aprocessing unit, being connected to the oscillator and the oscillationdetection sensor, for (1) obtaining time-frequency transformation databy performing a time-frequency transformation to the broadband Lamb wavedetected by the oscillation detection sensor, wherein the time-frequencytransformation data indicates a propagation time of the at least onemode of Lamb wave, and the propagation time is the time for Lamb wave topropagate from the oscillator through the oscillation detection sensor,and (2) identifying, based on the propagation time of the at least onemode of Lamb wave in the time-frequency transformation data, whether ornot the damage has occurred on or within the object, and/or identifyingthe size or length of the damage that occurred on or within the object.2. The system for damage diagnosis according to claim 1, wherein theprocessing unit, in the identifying process (2), based on whether or notthe propagation time of the at least one mode of Lamb wave matches areference value, identifies whether or not the damage has occurred on orwithin the object, and/or identifies the size or length of the damagethat occurred on or within the object.
 3. The system for damagediagnosis according to claim 1, wherein the broadband Lamb wave includestwo or more modes of Lamb waves; and the processing unit, in theidentifying process (2), based on whether or not the propagation time ofat least one mode of Lamb wave of the two or more modes of Lamb wavesmatches a reference value, identifies whether or not damage has occurredin the object, and/or identifies the size or length of the damage thatoccurred on or within the object.
 4. The system for damage diagnosisaccording to claim 3, wherein the identifying process (2) comprises aselection step for selecting the at least one mode Lamb wave from thetwo or more modes of Lamb waves to be compared with the reference value.5. The system for damage diagnosis according to claim 1, wherein thetime-frequency transformation data obtained by the processing unit is atwo-dimensional propagation intensity distribution data in whichfrequency is one of the two dimension and propagation time is the other.6. The system for damage diagnosis according to claim 1, wherein the atleast one mode Lamb wave includes a plurality of waves having mutuallydifferent frequencies; and the propagation time of the at least one modeof Lamb wave is a propagation time of a maximum intensity portion of atleast one of the plurality of waves.
 7. The system for damage diagnosisaccording to claim 1, wherein said at least one mode is A1 mode.
 8. Thesystem for damage diagnosis according to claim 1, wherein said at leastone mode is S0 mode and S1 mode.
 9. The system for damage diagnosisaccording to claim 1, wherein said at least one mode is A1 mode, S0mode, and S0 mode.
 10. The system for damage diagnosis according toclaim 1, wherein the at least one mode Lamb wave includes a plurality ofwaves having mutually different frequencies; and the processing unit, inthe identifying process (2), calculates propagation times of two of theplurality of waves, calculates a change ratio of the propagation timesby means of dividing a difference of the two propagation times by adifference of the frequencies of the two waves, and based on whether ornot the change ratio matches a reference value, identifies whether ornot the damage has occurred on or within the object, and/or identifiesthe size or length of the damage that occurred on or within the object.11. The system for damage diagnosis according to claim 10, wherein saidat least one mode is A1 mode.
 12. The system for damage diagnosisaccording to claim 4, wherein the system comprises two oscillators, withone oscillator being attached to one surface in the thickness directionof the object, and the other oscillator being attached to the othersurface in the thickness direction of the object; and the processingunit executes an oscillation control process to control the oscillators,and executes the oscillation control process and the selection stepunder any of the conditions (a) to (c) below, where condition (a) issuch that the processing unit, in the oscillation control process,controls the two oscillators so that a symmetrical mode Lamb wave isgenerated in the object, and selects the symmetric mode Lamb wave in theselection process; condition (b) is such that the processing unit, inthe oscillation control process, controls the two oscillators so that anasymmetric mode Lamb wave is generated in the object, and selects theasymmetric mode Lamb wave in the selection process; and condition (c) issuch that the processing unit executes the processes under conditions(a) and the processes under condition (b) at different times.
 13. Thesystem for damage diagnosis according to claim 4, wherein this systemcomprises two oscillation detection sensors, with one oscillationdetection sensor being attached to one surface in the thicknessdirection of the object, and the other oscillation detection sensorbeing attached to the other surface in the thickness direction of theobject; and the processing unit executes the processes (1) and (2) underany one of the conditions (a) to (c) below; where condition (a) is suchthat the processing unit, in the obtaining process (1), creates data inwhich an asymmetric mode is canceled out and a symmetric mode isemphasized by adding the broadband Lamb waves detected by the twooscillation detection sensors, and then the processing unit obtainstime-frequency transformation data by performing the time-frequencytransformation to the created data, and in the identifying process (2),selects a symmetric mode Lamb wave; condition (b) is such that theprocessing unit, in the obtaining process (1), creates data in which thesymmetric mode is canceled out and the asymmetric mode is emphasized bysubtracting the broadband Lamb waves detected by the two oscillationdetection sensors, and then the processing unit obtains time-frequencytransformation data by performing the time-frequency transformation tothe created data, and in the identifying process (2), selects anasymmetric mode Lamb wave; and condition (c) is such that the processingunit executes the processes under conditions (a) and the processes undercondition (b).
 14. The system for damage diagnosis according to claim 1,wherein the time-frequency transformation is any one of the wavelettransformation, short-time Fourier transformation, chirplettransformation, Wigner transformation, and Stockwell transformation, ora combination of any two or more of said transformations.
 15. The systemfor damage diagnosis according to claim 1, wherein the oscillator isattached to the object.
 16. The system for damage diagnosis according toclaim 1, wherein the oscillation detection sensor is attached to theobject.
 17. A method for damage diagnosis for diagnosing damage thatoccurred on or within an object, the method using an oscillator forapplying a broadband ultrasonic oscillation to the object to generate abroadband Lamb wave within the object, an oscillation detection sensorfor detecting the broadband Lamb wave from the object, the detectedbroadband Lamb wave including at least one mode of Lamb wave, and aprocessing unit being connected to the oscillator and the oscillationdetection sensor, and the method comprises the steps of: (1) obtainingtime-frequency transformation data by performing a time-frequencytransformation to the broadband Lamb wave detected by the oscillationdetection sensor, wherein the time-frequency transformation dataindicates a propagation time of the at least one mode of Lamp wave, andthe propagation time is the time for Lamb wave to propagate from theoscillator through the oscillation detection sensor; and (2)identifying, based on the propagation time of the at least one mode ofLamb wave in the time-frequency transformation data, whether or not thedamage has occurred on or within the object, and/or identifying the sizeor length of damage that occurred on or within the object.
 18. Themethod for damage diagnosis according to claim 17, wherein thetime-frequency transformation is any one of the wavelet transformation,short-time Fourier transformation, chirplet transformation, Wignertransformation, and Stockwell transformation, or a combination of anytwo or more of said transformations.